this post was submitted on 07 Aug 2023
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From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models https://aclanthology.org/2023.acl-long.656.pdf

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[–] [email protected] 2 points 11 months ago (4 children)

Not trying to be a smartass, but what's the alternative?

[–] [email protected] 8 points 11 months ago

Does there have to be one? It'd be nice if there were, of course, but this is currently the only way we know of to make these AIs.

[–] [email protected] 5 points 11 months ago (1 children)

Well, you can focus on rule-based/expert system style AI, a la WolframAlpha. Actually build algorithms to answer questions that are based on scientific fact and theory, rather than an approximated consensus of many sources of dubious origin.

[–] [email protected] 3 points 11 months ago

Ooo, old school AI 😍

In our current cultural consciousness, I'm not sure that even qualifies as AI anymore. It's all about neutral networks and machine learning nowadays.

[–] [email protected] 4 points 11 months ago (1 children)

I guess shoving an encyclopedia into it. I'm not sure really, it is a good point. Perhaps AI bias is as inevitable as human bias...

[–] [email protected] 8 points 11 months ago (1 children)

Despite what you might assume, an encyclopedia wouldn't be free from bias. It might not be as biased as, say, getting your training data from a dump of 4chan, but it'd absolutely still have bias. As an on-the-nose example, think about the definition of homosexuality; training on an older encyclopedia would mean the AI now thinks homosexuality is a crime.

[–] [email protected] 4 points 11 months ago

And imagine how badly most encyclopedias would reflect on languages and cultures other than the one that made them.

[–] [email protected] 2 points 11 months ago

The alternative is being extremely careful about what data you allow the LLM to learn from. Then it would have your bias, but hopefully that'll be a less flagrantly racist bias.